Epidemics on random graphs with tunable clustering

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dc.creatorBritton, Tom
dc.creatorDeijfen, Maria
dc.creatorLagerås, Andreas Nordvall
dc.creatorLindholm, Mathias
dc.date2007-08-29
dc.date.accessioned2026-07-07T08:26:23Z
dc.date.available2026-07-07T08:26:23Z
dc.descriptionIn this paper, a branching process approximation for the spread of a Reed-Frost epidemic on a network with tunable clustering is derived. The approximation gives rise to expressions for the epidemic threshold and the probability of a large outbreak in the epidemic. It is investigated how these quantities varies with the clustering in the graph and it turns out for instance that, as the clustering increases, the epidemic threshold decreases. The network is modelled by a random intersection graph, in which individuals are independently members of a number of groups and two individuals are linked to each other if and only if they share at least one group.
dc.description17 pages, 1 figure
dc.identifierhttps://arxiv.org/abs/0708.3939
dc.identifierhttp://arxiv.org/abs/0708.3939
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/136923
dc.subjectProbability
dc.subject92D30, 05C80
dc.titleEpidemics on random graphs with tunable clustering
dc.typetext

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